Borrowing it
Nothing to install: this file belongs to Nam-Cheol/namba-ai. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/Nam-Cheol/namba-ai/main/.agents/skills/namba-plan/SKILL.mdgit clone --depth 1 https://github.com/Nam-Cheol/namba-aiWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/nam-cheol/namba-ai/namba-plan)<a href="https://agentmods.dev/skills/nam-cheol/namba-ai/namba-plan"><img src="https://agentmods.dev/badge/skills/nam-cheol/namba-ai/namba-plan/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/nam-cheol/namba-ai/namba-plan"><img src="https://agentmods.dev/badge/skills/nam-cheol/namba-ai/namba-plan.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00016 | $0.01160 |
| Opus 5 | $0.00008 | $0.00580 |
| Sonnet 5 | $0.00003 | $0.00232 |
| Haiku 4.5 | $0.00002 | $0.00116 |
Grade A, and why
namba-plan scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 12d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 42 lines — stays where its author put it; the contents beside it link to each section on GitHub.
State effect: mutating workflow entry point. Use help/probe paths read-only, and otherwise expect repository state or GitHub state to change.
Generated instruction contract for this command skill:
- Purpose: keep the role or command scope explicit, bounded, and testable.
- Boundary: honor read-only versus mutating state effects, configured sandbox mode, and assigned file or workflow ownership.
- Required output: report concrete actions, changed paths or artifacts, validation evidence, and pass/fail status or blockers.
- Pass/fail criteria: claim success only when acceptance criteria and configured validation are satisfied; otherwise name the exact blocker and impact.
- Evidence expectations: cite source artifacts such as SPEC files,
.namba/configs, diffs, test output, PR/check links, or generated manifests instead of relying on unsupported assertions. - Security responsibilities: never expose or commit secrets; treat auth, privacy, destructive commands, permission changes, and external network or credential use as security-sensitive.
- Destructive command and escalation policy: do not run destructive commands unless explicitly requested; request approval for privileged, networked, or sandbox-blocked actions only when the active approval mode allows it, and otherwise report the blocker or use a safe non-escalating path.
- Fallback implementer boundary: if a specialist path is unavailable and the main/default implementer takes over, stay within the assigned scope and preserve the same evidence and validation duties.
- Portability: keep durable guidance non-project-specific unless the current repository config or SPEC explicitly provides the project detail.
Use this skill when the user explicitly says $namba-plan, namba plan, or asks to create a new feature SPEC package.
Behavior:
- Before reading project docs, checking Git state, or running the CLI, run the Namba clarification gate on the user's raw request.
- If the request is short, broad, or missing target surface, user flow, scope boundaries, constraints, acceptance criteria, or validation, do not run
namba planyet. Ask 1-3 concise questions first;게시판 만들어줘is the canonical example that must ask questions before planning. - Treat Codex Plan mode as the preferred clarification surface and
namba planas the executor: when native Plan mode choice UI is available, use it to ask the clarification questions before any CLI command. - The Plan mode output must be converted into a refined description shaped as Goal, Scope, Constraints, and Acceptance, then passed to
namba plan "<refined description>". - Repo hooks and skills cannot force Codex to switch modes by themselves; if native Plan mode UI is unavailable in the current session, fall back to concise text questions in chat instead of inventing a CLI wizard.
- Continue the clarification loop across turns until you can restate the request as Goal, Scope, Constraints, and Acceptance. Only then invoke the CLI with the refined description.
- Prefer the installed
namba planCLI when available. - Keep
namba planfor feature-oriented SPEC work; usenamba harnesswhen the request is about reusable agent, skill, workflow, or orchestration scaffolding; use$namba-createwhen the user wants the repo-local skill or custom-agent artifact itself instead of another SPEC. - When repo-managed MCP presets are configured, prefer them for planning context before broader web search; for example, use
context7for library and framework docs,sequential-thinkingfor deeper decomposition, andplaywrightfor browser-verified flows. - Read
.namba/project/product.md,.namba/project/tech.md,.namba/project/mismatch-report.md,.namba/project/quality-report.md, and any relevant.namba/project/systems/*.mdartifacts before drafting the SPEC. - Treat executable code and authoritative config as stronger planning evidence than docs, and preserve code-vs-doc conflicts instead of smoothing them out.
- Keep planning in the current workspace. When branch-per-work is enabled, create or switch to the dedicated
spec/...branch before writing.namba/specs/<SPEC>/. - Use
--current-workspaceonly when the user intentionally wants to scaffold on the current branch without creating a dedicated SPEC branch. - Do not create a planning worktree. Reserve temporary worktrees for overlapping
namba run SPEC-XXX --parallelexecution, and expect them to disappear after the run finishes cleanly. - Create the next sequential
SPEC-XXXpackage under.namba/specs/after that branch decision is explicit. - Seed
.namba/specs/<SPEC>/reviews/with product, engineering, design, and aggregate readiness artifacts. - Unless the invocation includes
--no-review, treat the created SPEC as an automatic handoff and immediately continue with$namba-plan-review SPEC-XXXafter the CLI prints the new SPEC ID. - After the automatic handoff, read
.namba/specs/<SPEC>/reviews/readiness.md; if it does not sayCleared reviews: 3/3, do not treat planning as complete. Continue with$namba-plan-review SPEC-XXXagain, or run the missing$namba-plan-pm-review,$namba-plan-eng-review, and$namba-plan-design-reviewtracks before implementation. - When
--no-reviewis present, stop after scaffold creation and point any later review work to$namba-plan-pm-review,$namba-plan-eng-review, and$namba-plan-design-review, or$namba-plan-review SPEC-XXX. - Keep the scope concrete and implementation-ready.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 12d ago First seen · 42 lines · 16 tokens per session scan A 653f76505aaf
namba-plan is a skill published in the GitHub repository Nam-Cheol/namba-ai (11 stars, last pushed 20d ago), licensed MIT. It adds 16 tokens to every session and 1,160 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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